# Tag Archives: viz

# 02 Jun 2021

# 05 Apr 2021

# 29 Mar – 01 Apr 2021

- (abs, pdf) Sivitilli et al.,
*Virtual Reality and Immersive Collaborative Environments: the New Frontier for Big Data Visualisation* - (abs, pdf) Tomaselli & Ferrara,
*Lyman-alpha radiation pressure: an analytical exploration* - (abs, pdf) Stefanon et al.,
*Galaxy Stellar Mass Functions from z~10 to z~6 using the Deepest Spitzer/IRAC Data: No Significant Evolution in the Stellar-to-Halo Mass Ratio of Galaxies in the First Gyr of Cosmic Time* - (abs, pdf) Foucart et al.,
*Implementation of Monte-Carlo transport in the general relativistic SpEC code* - (abs, pdf) Becker et al.,
*The mean free path of ionizing photons at 5 < z < 6: evidence for rapid evolution near reionization* - (abs, pdf) Chiti et al.,
*The Metal-Poor Metallicity Distribution of the Ancient Milky Way* - (abs, pdf) Chiti et al.,
*Stellar Metallicities from SkyMapper Photometry II: Precise photometric metallicities of $\sim$280,000 giant stars with [Fe/H] $< -0.75$ in the Milky Way*

# 04 Feb 2021

- (abs, pdf) Lane et al.,
*The Cosmological Trajectories Method: Modelling cosmic structure formation in the non-linear regime* - (abs, pdf) Hauschildt & Baron,
*A 3D radiative transfer framework: XII. Many-core, vector and GPU methods* - (abs, pdf) Dykes et al.,
*3D Modelling and Visualisation of Observed Galaxies*

# 21-23 Dec 2020

- (abs, pdf) Nolan et al.,
*Interactive Cosmology Visualization Using the Hubble UltraDeep Field Data in the Classroom* - (abs, pdf) Jeon et al.,
*The role of faint population III supernovae in forming CEMP stars in ultra-faint dwarf galaxies* - (abs, pdf) Tseng et al.,
*An adaptive mesh, GPU-accelerated, and error minimized special relativistic hydrodynamics code* - (abs, pdf) Patrick et al.,
*The Collapse of Atomically-Cooled Primordial Haloes. I. High Lyman-Werner Backgrounds* - (abs, pdf) Ouchi,
*Observations of Ly$\alpha$ Emitters at High Redshift*

# 08 Oct 2020

- (abs, pdf) Turner et al.,
*The Onset of Gravothermal Core Collapse in Velocity Dependent Self-Interacting Dark Matter Subhaloes* - (abs, pdf) Dai & Seljak,
*Learning effective physical laws for generating cosmological hydrodynamics with Lagrangian Deep Learning* - (abs, pdf) Marsden & Shankar,
*Using Unreal Engine to Visualize a Cosmological Volume* - (abs, pdf) Hennebelle et al.,
*What is the role of stellar radiative feedback in setting the stellar mass spectrum?*

# 09 Mar 2020

- (abs, pdf) Machida & Basu,
*Different Modes of Star Formation II: Gas Accretion Phase of Initially Subcritical Star-Forming Clouds* - (abs, pdf) Tallada et al.,
*CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop* - (abs, pdf) Goz et al.,
*Performance and energy footprint assessment of FPGAs and GPUs on HPC systems using Astrophysics application* - (abs, pdf) Elias et al.,
*Cosmological insights into the assembly of the radial and compact stellar halo of the Milky Way* - (abs, pdf) Lee & Hopkins,
*Most Stars (and Planets?) Are Born in Intense Radiation Fields*

# 06 Dec 2019

- (abs, pdf) Kirby et al.,
*Elemental Abundances in M31: The Kinematics and Chemical Evolution of Dwarf Spheroidal Satellite Galaxies* - (abs, pdf) Orlando et al.,
*3DMAP-VR, a project to visualize 3-dimensional models of astrophysical phenomena in virtual reality* - (abs, pdf) Shingles et al.,
*Monte Carlo radiative transfer for the nebular phase of Type Ia supernovae*

# 18 Oct 2019

- (abs, pdf) Yuan et al.,
*Dynamical Relics of the Ancient Galactic Halo* - (abs, pdf) Hassan et al.,
*Testing Galaxy Formation Simulations with Damped Lyman-${\alpha}$ Abundance and Metallicity Evolution* - (abs, pdf) Luo et al.,
*Direct collapse to supermassive black hole seeds: the critical conditions for suppression of $\rm H_2$ cooling* - (abs, pdf) Yip et al.,
*From Dark Matter to Galaxies with Convolutional Neural Networks* - (abs, pdf) Cielo et al.,
*Speeding simulation analysis up with yt and Intel Distribution for Python* - (abs, pdf) Tsizh et al.,
*Large-scale structures in the $\Lambda$CDM Universe: network analysis and machine learning* - (abs, pdf) Cielo et al.,
*Visualizing the world's largest turbulence simulation*